Insurance companies transfer a risk of loss in exchange for payment of a premium by the insured. In order to determine the amount of the premium, insurance companies attempt to determine the likelihood that a loss will occur. Ideally, insurance premiums should correlate with the frequency and severity of the potential exposure to risk. In the case of automobile insurance, for example, an insured's driving experience and actual driving record are factors that correlate with likelihood of loss.
In furtherance of anti-discrimination policies, many governments throughout the world impose restrictions on the types of factors that insurance companies may use to rate insurance. As one example, the State of California defines three mandatory ratings factors and several optional ratings factors to be used in establishing automobile insurance premiums. Only the approved list of factors may be used in determining premiums. These restrictions can result in insurance companies charging premiums that do not correlate as accurately as possible with potential risk of loss. In specific situations, insurance companies may undercharge certain potential insureds in view of the risk of loss.
Insurance companies define their profits as earned premiums plus investment income less incurred loss and underwriting expenses. An insurance company that charges less of a premium than is warranted will recognize less profit. Conversely, an insurance company that charges a higher premium will recognize more profit. In a competitive market, price competition among insurers establishes an upper limit on the amount of premiums. An insurer can charge only the amount that an insured is willing to pay. Downward price pressure due to competition, particularly when coupled with restrictions on the ability to more accurately rate insurance risks, results in insurance companies charging suboptimal premiums and, therefore, obtaining suboptimal profits.
The prior art includes a description of determining types of profitability information for certain types of new or existing insurance policies. For example, U.S. Patent Application No. 2002/0161609 A1, filed by Zizzamia et al. and published on Oct. 31, 2002, describes a process of creating a predictive model to calculate a quantitative score for commercial insurance policies. The predictive model, in turn, requires “external data sources,” such as zip code level census data, county level data such as weather, and business owner household level demographics to compute profitability information (see paragraphs 13, 35-41). In the absence of such external data, the methods of Zizzamia could not determine expected profitability. In addition, the Zizzamia application refers to a “score,” calculated from external data sources, but it does not describe the score as being normalized across different discrete books of business. Rather, the Zizzamia application uses the calculated score to sort a particular policy into one of ten deciles, for which a particular loss ratio has been determined (see paragraphs 93-94). Zizzamia does not provide any description as to how profitability information may be calculated or used outside of the commercial insurance market.